Paper
1 May 1989 Optimization for Object Localization of the Constrained Algebraic Reconstruction Technique
K. M. Hanson
Author Affiliations +
Abstract
A method for optimizing image-recovery algorithms is presented that is based on how well the specified task of object localization can be performed using the reconstructed images. The task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, image recovery, and performance of the stated task based on the final image. This method is used to optimize the constrained Algebraic Reconstruction Technique (ART), which reconstructs images from their projections under a nonnegativity constraint by means of an iterative updating procedure. The optimization is performed by finding the the relaxation factor, which is employed in the updating procedure, that yields the minimum rms error in estimating the position of discs in the reconstructed images. It is found that the optimum operating points for the best object localization are essentially the same as those obtained earlier when the performance of simple object detection is to be optimized.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
K. M. Hanson "Optimization for Object Localization of the Constrained Algebraic Reconstruction Technique", Proc. SPIE 1090, Medical Imaging III: Image Formation, (1 May 1989); https://doi.org/10.1117/12.953199
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Cited by 10 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Adaptive optics

Image acquisition

Image processing

Medical imaging

Optimization (mathematics)

Imaging systems

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